Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
The cloud offers unprecedented access to computation. However, ensuring the privacy of that computation remains a significant challenge. In this paper, we address the problem of distributing computation onto the cloud in a way that preserves the privacy of the computation's data even from the cloud nodes themselves. The approach, called sTile, separates the computation into small subcomputations and distributes them in a way that makes it prohibitively hard to reconstruct the data. We evaluate sTile theoretically and empirically: First, we formally prove that sTile systems preserve privacy. Second, we deploy a prototype implementation on three different networks, including the globally-distributed PlanetLab testbed, to show that sTile is robust to network delay and efficient enough to significantly outperform existing privacy-preserving approaches.
Tiles, Assembly, Privacy, Crystals, Software systems, Data privacy, Computer architecture, sTile, privacy, privacy-preserving computation, private cloud computing, cloud, self-assembly, tile assembly model
Yuriy Brun, Nenad Medvidovic, "Keeping Data Private while Computing in the Cloud", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 285-294, doi:10.1109/CLOUD.2012.126